class_docstr: Handler for `VarLenFeature` values.
  
  `VarLenFeature` values will be parsed as an array of values of the
  corresponding dtype. In case the value is missing an empty array
  will be returned.
class_docstr_tok: ["Handler","for","`","VarLenFeature","`","values",".","`","VarLenFeature","`","values","will","be","parsed","as","an","array","of","values","of","the","corresponding","dtype",".","In","case","the","value","is","missing","an","empty","array","will","be","returned","."]
docstr: Encode the value of this feature into the CSV line.
docstr_tok: ["Encode","the","value","of","this","feature","into","the","CSV","line","."]
code: def encode_value(self, string_list, values):
      """Encode the value of this feature into the CSV line."""
      if self._encoder:
          string_list[self._index] = self._encoder.encode_record(values)
      else:
          string_list[self._index] = (
              _to_string(values[0]) if values else ""
          )
  
file_path: transform/tensorflow_transform/coders/csv_coder.py
imports: import csv
  import io
  import numpy
  import tensorflow
  from tensorflow_transform.tf_metadata import schema_utils
label_desc: Use image node_id 3 for calling the _VarLenFeatureHandler obj's underlying member method code with example usage: obj.encode_value(string_list, values) without return types